WEBVTT 1 00:00:02.910 --> 00:00:03.840 Hello students. 2 00:00:03.840 --> 00:00:07.623 Now, we are down to the last problem, problem 20. 3 00:00:08.490 --> 00:00:13.440 So, we already solved 20A, now we are going to solve 20B, 4 00:00:13.440 --> 00:00:18.440 and I have also added two extra sections here, C and D, 5 00:00:18.990 --> 00:00:20.670 even though they are not in your book 6 00:00:20.670 --> 00:00:22.380 because I do want to go over them. 7 00:00:22.380 --> 00:00:25.740 They're important, and as I mentioned previously, 8 00:00:25.740 --> 00:00:29.220 we are going to look at data sets where we have outliers. 9 00:00:29.220 --> 00:00:32.103 So, here the dataset is still the same. 10 00:00:33.750 --> 00:00:36.903 Part B is asking us to appropriately summarize the data. 11 00:00:38.340 --> 00:00:42.663 So, because we have an outlier here, 12 00:00:56.700 --> 00:00:59.583 to appropriately summarize the data, 13 00:01:01.290 --> 00:01:03.010 we are going to use the median 14 00:01:04.800 --> 00:01:09.093 and IQR, or interquartile range. 15 00:01:10.890 --> 00:01:14.310 So, that is the answer for B. 16 00:01:14.310 --> 00:01:16.170 So, what is the answer for C? 17 00:01:16.170 --> 00:01:18.480 I think you probably have guessed it, 18 00:01:18.480 --> 00:01:22.410 but I will nevertheless go through it 19 00:01:22.410 --> 00:01:24.480 and I'm gonna use a different color. 20 00:01:24.480 --> 00:01:28.530 So, C is asking us which measures, 21 00:01:28.530 --> 00:01:30.750 the mean or median is a better measure 22 00:01:30.750 --> 00:01:33.600 of a typical value, again, justify? 23 00:01:33.600 --> 00:01:38.040 So, for this dataset, we do have an outlier. 24 00:01:38.040 --> 00:01:41.283 So, as you may have thought, because we have an outlier, 25 00:01:43.380 --> 00:01:47.127 the better measure of a typical value will be median. 26 00:01:48.687 --> 00:01:53.687 So, due to an outlier that is present 27 00:01:54.570 --> 00:01:57.560 in this dataset is a better measure. 28 00:02:08.970 --> 00:02:12.360 And the last problem here is asking us, 29 00:02:12.360 --> 00:02:14.820 which measures, the standard deviation 30 00:02:14.820 --> 00:02:17.820 or interquartile range, or as we call it IQR, 31 00:02:17.820 --> 00:02:19.950 is a better measure of dispersion? 32 00:02:19.950 --> 00:02:24.090 And yes, if you have guessed IQR, you are correct. 33 00:02:24.090 --> 00:02:26.283 So, again, let me use another color. 34 00:02:28.020 --> 00:02:32.493 So, for D here, the answer will be again, due to an outlier, 35 00:02:41.229 --> 00:02:46.229 IQR a better measure of dispersion. 36 00:03:02.117 --> 00:03:06.543 So, due to the outlier, 37 00:03:08.400 --> 00:03:11.250 when we are summarizing the data, 38 00:03:11.250 --> 00:03:13.393 we want to use the median and the IQR 39 00:03:14.400 --> 00:03:18.450 and due to an outlier the median here is a better measure 40 00:03:18.450 --> 00:03:21.657 of a typical value, and again, due to an outlier, 41 00:03:21.657 --> 00:03:25.230 the IQR here is a better measure of dispersion. 42 00:03:25.230 --> 00:03:28.020 So, basically, the summary here is, 43 00:03:28.020 --> 00:03:31.590 whenever we have an outlier, 44 00:03:31.590 --> 00:03:36.590 median and IQR is our preferred statistics. 45 00:03:37.986 --> 00:03:40.110 And when we do not have an outlier, 46 00:03:40.110 --> 00:03:43.020 it's basically mean and standard deviation. 47 00:03:43.020 --> 00:03:47.910 So, again, mean median tells us the central tendency 48 00:03:47.910 --> 00:03:50.520 are how the data congregates, 49 00:03:50.520 --> 00:03:53.430 basically, what is the typical value of the dataset 50 00:03:53.430 --> 00:03:55.890 and IQR and standard deviation tells us 51 00:03:55.890 --> 00:03:57.753 the dispersion of the dataset. 52 00:03:58.800 --> 00:04:00.900 Hopefully, this was helpful 53 00:04:00.900 --> 00:04:04.560 and I know I have covered a number of examples here, 54 00:04:04.560 --> 00:04:05.970 and hopefully, this will be helpful, 55 00:04:05.970 --> 00:04:10.410 not only for you to solve the homework problems, 56 00:04:10.410 --> 00:04:11.823 but also for your test. 57 00:04:13.230 --> 00:04:15.150 The only other thing I'll be posting now 58 00:04:15.150 --> 00:04:18.450 from chapter four is the Excel file, 59 00:04:18.450 --> 00:04:21.510 which will show you how to basically 60 00:04:21.510 --> 00:04:24.450 create the order data set by basically one click. 61 00:04:24.450 --> 00:04:26.340 It's very simple, very easy 62 00:04:26.340 --> 00:04:31.340 and I do want you, for you to get familiar with Excel, 63 00:04:31.620 --> 00:04:33.240 but again, it is not required 64 00:04:33.240 --> 00:04:35.370 that you use Excel for this class. 65 00:04:35.370 --> 00:04:37.020 I just like to introduce Excel 66 00:04:37.020 --> 00:04:41.220 because it's widely available and it's pretty easy to use, 67 00:04:41.220 --> 00:04:42.990 and that's why I kind of introduce it. 68 00:04:42.990 --> 00:04:44.940 But again, if you do not want to use it 69 00:04:44.940 --> 00:04:46.240 you do not have to use it. 70 00:04:47.430 --> 00:04:51.903 Okay, so I will see you soon again with the Excel file.